{"id":"W4396935741","doi":"10.1007/s00261-024-04346-0","title":"Combination of clinical and spectral-CT iodine concentration for predicting liver metastasis in gastric cancer: a preliminary study","year":2024,"lang":"en","type":"article","venue":"Abdominal Radiology","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Natural Science Foundation of China","keywords":"Medicine; Receiver operating characteristic; Metastasis; Cancer; Hepatology; Internal medicine; Iodine; Carcinoembryonic antigen; Logistic regression; Stomach cancer; Gastroenterology; Area under the curve; Radiology; Oncology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004325033,0.00009920005,0.0002918359,0.00008743528,0.00002321238,0.000007973553,0.00004924491,0.00003192031,0.00001015146],"category_scores_gemma":[0.00009176778,0.0000975517,0.00004398453,0.0001451921,0.00006704694,0.000133808,0.00001264557,0.0001627389,5.708645e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003613719,"about_ca_system_score_gemma":0.00002380403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000305185,"about_ca_topic_score_gemma":0.00002564634,"domain_scores_codex":[0.9991083,0.00007123728,0.0004112088,0.0001905557,0.00005053195,0.0001681338],"domain_scores_gemma":[0.9993623,0.00047934,0.00004138667,0.00006525683,0.00002065225,0.00003106555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001178721,0.0003869335,0.4148364,0.0008797926,0.0005053022,0.0002672613,0.003905759,0.0364008,0.004042147,0.001723959,0.0003321918,0.5355407],"study_design_scores_gemma":[0.002798102,0.001617924,0.1581358,0.0001323334,0.0002442,0.0001865075,0.001091951,0.8334553,0.001412018,0.0005750357,0.0001735019,0.0001773149],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9773408,0.005929545,0.01570442,0.0000506769,0.0003814313,0.0004649199,0.00001457632,0.00005508778,0.00005854783],"genre_scores_gemma":[0.9976602,0.0006627709,0.001450047,0.000007816816,0.0001061509,0.00008436604,0.000007517122,0.00001373463,0.000007404592],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7970545,"threshold_uncertainty_score":0.3978043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02568019273515553,"score_gpt":0.3272540813971357,"score_spread":0.3015738886619802,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}